Applied N F Interpolation Method for Recover Randomly Missing Values in Data Mining

Abstract

Data cleansing is a critical step for data preparation. The values lost in the database are a common problem faced by data analysts. Missing values in data mining are continual troubles that can grounds errors in data analysis. Randomly missing elements in the attribute/dataset make data analysis complicated and also confused to consolidated result. It affects the accuracy of the result and intermediate queries. By using statistical/numerical methods, one can recover the missing data and decrease the suspiciousness in the database. The present paper gives an applied approach of Newton forward interpolation (NFI) method to recover the missing values.